Which techniques will help mitigate this exception?

An application is processing clickstream data using Amazon Kinesis. The clickstream data feed into Kinesis experiences periodic spikes.

The PutRecords API call occasionally fails and the logs show that the failed call returns the response shown below:

Which techniques will help mitigate this exception? (Choose two.)
A . Implement retries with exponential backoff.
B . Use a PutRecord API instead of PutRecords.
C . Reduce the frequency and/or size of the requests.
D . Use Amazon SNS instead of Kinesis.
E . Reduce the number of KCL consumers.

View Answer

Answer: AC

Explanation:

The response from the API call indicates that the ProvisionedThroughputExceededException exception has occurred. This exception means that the rate of incoming requests exceeds the throughput limit for one or more shards in a stream.

To mitigate this exception, the developer can use one or more of the following techniques:

Implement retries with exponential backoff. This will introduce randomness in the retry intervals and avoid overwhelming the shards with retries.

Reduce the frequency and/or size of the requests. This will reduce the load on the shards and avoid throttling errors.

Increase the number of shards in the stream. This will increase the throughput capacity of the stream and accommodate higher request rates.

Use a PutRecord API instead of PutRecords. This will reduce the number of records per request and

avoid exceeding the payload limit.

Reference:

[ProvisionedThroughputExceededException – Amazon Kinesis Data Streams Service API Reference] [Best Practices for Handling Kinesis Data Streams Errors]